Spatial Color Indexing: A Novel Approach for Content-Based Image Retrieval

This paper examines the use of a computational geometry-based spatial color indexing methodology for efficient and effective image retrieval. In this scheme, an image is evenly divided into a number of M*N nonoverlapping blocks, and each individual block is abstracted as a unique feature point labeled with its spatial location, dominant hue, and dominant saturation. For each set of feature points labeled with the same hue or saturation, we construct a Delaunay triangulation and then compute the feature point histogram by discretizing and counting the angles produced by this triangulation. The concatenation of all these feature point histograms serves as the image index. An important contribution of this work is to encode the spatial color information using geometric triangulation, which is translation, rotation, and scale independent. We have implemented the proposed approach and have tested it over two image collections of 2000 JPEG images and 1380 GIF images. Various experimental results demonstrate the efficacy of our techniques.